Aside

Contact Info

Skills

Programming: R, Python, SQL

Data Science: Statistical modelling and data vizualization. Main experience with frequentist methods, but with high interest to develop in bayesian’s.

Disclaimer

This resume was made with the R package pagedown.

Last updated on 2019-12-18.

Main

Carlos A. Haro

Economist with experience in data science

Main focus on data visualization and supervised learning.

Education

(ITAM) Instituto Tecnológico Autónomo de México

B.S., Economics

Mexico City, Mexico

2014 - 2018

Experience

Sr. Data Scientist

Mexico’s Central Tax Administration Office
(Servicio de Administración Tributaria)

Mexico City

Jan. 2019 - present

  • Development and deployment of a supervised model for classifying tax debt | R (tidyverse, ranger), Python (scikit-learn, pandas), SQL
  • Designed and taught three courses for the institution’s staff training: introduction to R, basics of exploratory data analysis, building data science pipelines using Makefiles | R (tidyverse, ggplot2), GNU Make
  • Designed a pipeline for automatic generation of frequent data visualization reports | R Markdown (ggplot2, shiny)
  • Perform network analysis to detect tax evasion communities | R (tidyverse, visnetwork, ggraph)
  • Version control of cloropleth maps for the geographical display of taxpayer’s data | R (leaflet QGis)

Jr. Data Scientist | Economic Analyst

EnergeA
(Energy Sector Consulting Firm)

Mexico City

2018

  • Developed a statistical model for identifying anti-competitive practices between the mid-stream natural gas providers | R
  • Neighboring gas station’s competition analysis for identifying price setting mechanisms. | R
  • Built a PDF scrapping pipeline of 100+ files for ownership analysis of Mexico’s natural gas industry. | R (stringr, selenium)

Miscellaneous

Hackaton challenge winner

Annual BBVA Hackaton Challenge

N/A

2019

Organizer: BBVA Bank
Challenge: Update and insert operation of a 50 million observations dataset in under 10 minutes.
Result: 95%+ accuracy of update and insert achieved in 4 minutes | Pyspark on AWS for the algorithm, RMarkdown for the report

Hackaton participant

Annual Banamex Hackaton Challenge

N/A

2019

Organizer: Banamex Bank
Challenge: Create any platform for aiding small mexican businesses (< 75,000 usd/year cash flow) flourish.
Result: Created a live dashboard service that calculated the probability of succes of a business given initial investment, number of employees, employee salary, etc. | R (shiny), Python (scikit-learn), AWS